Multiple choice strategy - A novel approach for particle swarm optimization - Preliminary study

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan

Název:

Autor:

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan

Typ dokumentu:

Článek ve sborníku (English)

Zdrojový dok.:

Artificial Intelligence and Soft Computing 2014, Part II. 2013, vol. 7895 LNAI, issue PART 2, p. 36-45

ISSN:

0302-9743 (Sherpa/RoMEO, JCR)

Journal Impact This chart shows the development of journal-level impact metrics in time

JCR	Journal Citation Reports - Impact Factor
SNIP	SCImago Source Normalized Impact per Paper
SJR	SCImago Journal Rank
IPP	SCImago Impact per Publication
CS	Scopus CiteScore

(Note: The metrics are not comparable against one another.)

ISBN:

978-3-642-38609-1

DOI:

https://doi.org/10.1007/978-3-642-38610-7_4

Abstrakt:

In this paper, a new promising strategy for PSO algorithm is proposed and described. This strategy presents alternative way of assigning new velocity to each particle in population. This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on four different test functions and the promising results of this alternative strategy are compared with the classic method.

Plný text:

https://link.springer.com/chapter/10.1007/978-3-642-38610-7_4

Zobrazit celý záznam

Soubory tohoto záznamu

Název: Fulltext_1003578.pdf

Velikost: 389.7Kb

Formát: PDF

Popis: fulltext

Citace ČSN ISO 690:2011

Citace článku v konferenčním sborníku:
PLUHÁČEK, Michal, Roman ŠENKEŘÍK a Ivan ZELINKA. Multiple choice strategy - A novel approach for particle swarm optimization - Preliminary study. In: Artificial Intelligence and Soft Computing 2014, Part II [online]. Zakopane: Springer-Verlag Berlin, 2013, s. 36-45. [cit. 2024-04-17]. ISSN 0302-9743. Dostupné z: https://link.springer.com/chapter/10.1007/978-3-642-38610-7_4.

Tyto citace vytvořil software a mohou obsahovat chyby. Pro ověření přesnosti si nastudujte příslušnou citační normu nebo příručku.